Measurement and data-processing approaches related to enzyme reaction-based biosensors have historically been based on evaluation of current versus time profiles. Limitations of such analyses include adverse influences on measured values due to changes in experimental variables that influence (a) rates of chemical reactions and (b) physical processes that control the response.
Similar problems have been encountered in conventional kinetic-based methods when they are applied to enzymatic determinations of analytes in homogeneous solutions (Chen, W., et al., Analytica Chimica Acta 388:231-241, 1999). Results of such analyses generally have limited ranges of linearity and are influenced by experimental variables that affect enzyme activity. Data-analysis methods applied to enzyme reaction-based sensors are influenced by variables that affect rates of reaction and rates of mass transport. However, application of initial-rate methods using enzymes in homogenous solution (i.e., kinetic-based solution methods) tend to be influenced only by variables that affect rates of reactions.
A variety of measurement and data-processing approaches have been used in attempts to reduce or eliminate problems in homogenous solution measurement of analyte concentrations including, but not limited to, the following approaches. Engh, et al., (Anal. Chem. 60:545, 1988), used alternative applications of a rate-based approach and showed improvement in the ruggedness of enzymatic methods but also demonstrated that the methods did little to improve the sensitivity at high concentrations of substrate. For homogenous solution analyses, a two-rate method (Wentzell, P. D., et al, Anal. Chem. 58:2851, 1986) and pseudoequilibrium methods (Meiling, G. E., et al., Anal. Chem. 50:1611, 1978; Harris, R. C., Clin. Chem. 29:2079, 1983) have demonstrated the potential to reduce dependencies on experimental variables to a similar degree as has been seen with equilibrium methods.
Two-rate and pseudoequilibrium methods (based on homogenous system methods) have been applied to enzyme reaction-based biosensor methods to determine if these methods could be adapted to biosensors such that measurement improvements would be seen which were similar to those achieved in homogenous solution (Chen, et al., Analytica Chimica Acta 388:231-241, 1999; Wentzell, P. D., et al, Anal. Chem. 58:2851, 1986; Meiling, G. E., et al., Anal. Chem. 50:1611, 1978; Harris, R. C., Clin. Chem. 29:2079, 1983). The enzyme reaction-based biosensor typically used in such studies consisted of an enzyme and an electron mediator immobilized on the surface of a glassy-carbon electrode (e.g., Chen, et al., Analytica Chimica Acta 388:231-241, 1999). Although some improvements in performance characteristics of the enzyme reaction-based biosensor were observed, both methods were shown to have limitations when applied to enzyme reaction-based biosensor data.
Published U.S. Patent Application No. US/2002/0026110 and PCT International Patent Application No. WO 0188534 describe methods for improving performance and reliability of biosensors using a predictive-kinetic (PK) method for data processing of a sensor-generated signal. In these methods, data from a transient region of a signal is used with suitable models and curve-fitting methods to predict the signal that would be measured for the system at the completion of the reaction.
In analyte monitoring devices that employ an electrochemical sensor, signal decay over time can be a significant problem. One method of dealing with signal decay as been to use algorithms that provide signal processing that allow for compensation of signal decay. One such signal processing algorithm is called Mixtures of Experts (MOE) (see, e.g., Kurnik, R. T., Sensors and Actuators B 60, 1 (1999); and U.S. Pat. Nos. 6,180,416, and 6,326,160). However, even current MOE methods only compensate to some extent for signal decay. Typically, standard MOE compensation becomes insufficient, for example, towards the end of long monitoring periods.
The present invention offers methods of improving performance of analyte monitoring systems, for example, that supply a series of analyte-related signals over time. Although aspects of the present invention initially use a similar principle and processing techniques to fit a curve and model the transient data, the present invention employs the fitted variables in a different manner to extract the relevant information. Unlike previous methods employing Predictive Kinetics (PK), one aspect of the present invention employs information from the time constants of exponential functions and pre-exponential terms to provide signal-decay corrections and to predict analyte values. Further methods of improving the performance of analyte monitoring systems are also disclosed.